Struct NNOptimizerStochasticGradientDescent

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pub struct NNOptimizerStochasticGradientDescent { /* private fields */ }

Expand description

Wraps MPSNNOptimizerStochasticGradientDescent.

Implementations§

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impl NNOptimizerStochasticGradientDescent

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pub const fn as_ptr(&self) -> *mut c_void

Returns the retained Objective-C pointer backing this wrapper.

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impl NNOptimizerStochasticGradientDescent

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pub fn learning_rate(&self) -> f32

Wraps the corresponding Metal Performance Shaders method.

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pub fn set_learning_rate(&self, value: f32)

Wraps the corresponding Metal Performance Shaders method.

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pub fn gradient_rescale(&self) -> f32

Wraps the corresponding Metal Performance Shaders method.

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pub fn apply_gradient_clipping(&self) -> bool

Wraps the corresponding Metal Performance Shaders method.

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pub fn set_apply_gradient_clipping(&self, value: bool)

Wraps the corresponding Metal Performance Shaders method.

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pub fn gradient_clip_max(&self) -> f32

Wraps the corresponding Metal Performance Shaders method.

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pub fn gradient_clip_min(&self) -> f32

Wraps the corresponding Metal Performance Shaders method.

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pub fn regularization_scale(&self) -> f32

Wraps the corresponding Metal Performance Shaders method.

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pub fn regularization_type(&self) -> usize

Wraps the corresponding Metal Performance Shaders method.

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impl NNOptimizerStochasticGradientDescent

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pub fn new(device: &MetalDevice, learning_rate: f32) -> Option<Self>

Wraps a constructor on MPSNNOptimizerStochasticGradientDescent.

Examples found in repository ?

examples/07_optimizer_and_state.rs (line 66)

37fn main() {
38    let device = MetalDevice::system_default().expect("no Metal device available");
39    let queue = device.new_command_queue().expect("command queue");
40
41    let command_buffer = queue.new_command_buffer().expect("command buffer");
42    let temporary_a =
43        State::temporary_with_buffer_size(&command_buffer, 32).expect("temporary state a");
44    let temporary_b =
45        State::temporary_with_buffer_size(&command_buffer, 64).expect("temporary state b");
46    let unique_count =
47        state_batch_increment_read_count(&[&temporary_a, &temporary_a, &temporary_b], 1);
48    assert_eq!(unique_count, 2);
49    assert_eq!(
50        temporary_a.resource_type_at_index(0),
51        state_resource_type::BUFFER
52    );
53    command_buffer.commit();
54    command_buffer.wait_until_completed();
55
56    let resource_list = StateResourceList::new().expect("resource list");
57    resource_list.append_buffer(16);
58    let persistent_state =
59        State::new_with_resource_list(&device, &resource_list).expect("persistent state");
60    assert_eq!(persistent_state.resource_count(), 1);
61    assert_eq!(persistent_state.buffer_size_at_index(0), 16);
62
63    let (gradient_buffer, gradient_vector) = vector_with_values(&device, &[0.1, -0.2]);
64    let (values_buffer, values_vector) = vector_with_values(&device, &[1.0, -1.0]);
65    let (result_buffer, result_vector) = vector_with_values(&device, &[0.0, 0.0]);
66    let optimizer = NNOptimizerStochasticGradientDescent::new(&device, 0.5).expect("sgd");
67    let base = optimizer.as_optimizer().expect("optimizer base");
68    assert_eq!(base.regularization_type(), nn_regularization_type::NONE);
69
70    let command_buffer = queue.new_command_buffer().expect("command buffer");
71    optimizer.encode_vector(
72        &command_buffer,
73        &gradient_vector,
74        &values_vector,
75        None,
76        &result_vector,
77    );
78    command_buffer.commit();
79    command_buffer.wait_until_completed();
80
81    let _ = gradient_buffer;
82    let _ = values_buffer;
83    let output = read_f32_values(&result_buffer, 2);
84    println!("{output:?}");
85}

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pub fn new_with_options( device: &MetalDevice, momentum_scale: f32, use_nesterov_momentum: bool, optimizer_descriptor: &NNOptimizerDescriptor, ) -> Option<Self>

Wraps a constructor on MPSNNOptimizerStochasticGradientDescent.

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pub fn as_optimizer(&self) -> Option<NNOptimizer>

Wraps the corresponding MPSNNOptimizerStochasticGradientDescent conversion helper.

Examples found in repository ?

examples/07_optimizer_and_state.rs (line 67)

37fn main() {
38    let device = MetalDevice::system_default().expect("no Metal device available");
39    let queue = device.new_command_queue().expect("command queue");
40
41    let command_buffer = queue.new_command_buffer().expect("command buffer");
42    let temporary_a =
43        State::temporary_with_buffer_size(&command_buffer, 32).expect("temporary state a");
44    let temporary_b =
45        State::temporary_with_buffer_size(&command_buffer, 64).expect("temporary state b");
46    let unique_count =
47        state_batch_increment_read_count(&[&temporary_a, &temporary_a, &temporary_b], 1);
48    assert_eq!(unique_count, 2);
49    assert_eq!(
50        temporary_a.resource_type_at_index(0),
51        state_resource_type::BUFFER
52    );
53    command_buffer.commit();
54    command_buffer.wait_until_completed();
55
56    let resource_list = StateResourceList::new().expect("resource list");
57    resource_list.append_buffer(16);
58    let persistent_state =
59        State::new_with_resource_list(&device, &resource_list).expect("persistent state");
60    assert_eq!(persistent_state.resource_count(), 1);
61    assert_eq!(persistent_state.buffer_size_at_index(0), 16);
62
63    let (gradient_buffer, gradient_vector) = vector_with_values(&device, &[0.1, -0.2]);
64    let (values_buffer, values_vector) = vector_with_values(&device, &[1.0, -1.0]);
65    let (result_buffer, result_vector) = vector_with_values(&device, &[0.0, 0.0]);
66    let optimizer = NNOptimizerStochasticGradientDescent::new(&device, 0.5).expect("sgd");
67    let base = optimizer.as_optimizer().expect("optimizer base");
68    assert_eq!(base.regularization_type(), nn_regularization_type::NONE);
69
70    let command_buffer = queue.new_command_buffer().expect("command buffer");
71    optimizer.encode_vector(
72        &command_buffer,
73        &gradient_vector,
74        &values_vector,
75        None,
76        &result_vector,
77    );
78    command_buffer.commit();
79    command_buffer.wait_until_completed();
80
81    let _ = gradient_buffer;
82    let _ = values_buffer;
83    let output = read_f32_values(&result_buffer, 2);
84    println!("{output:?}");
85}

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pub fn momentum_scale(&self) -> f32

Wraps the corresponding MPSNNOptimizerStochasticGradientDescent method.

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pub fn use_nesterov_momentum(&self) -> bool

Wraps the corresponding MPSNNOptimizerStochasticGradientDescent method.

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pub fn encode_vector( &self, command_buffer: &CommandBuffer, input_gradient_vector: &Vector, input_values_vector: &Vector, input_momentum_vector: Option<&Vector>, result_values_vector: &Vector, )

Wraps the corresponding MPSNNOptimizerStochasticGradientDescent encode entry point.

Examples found in repository ?

examples/07_optimizer_and_state.rs (lines 71-77)

37fn main() {
38    let device = MetalDevice::system_default().expect("no Metal device available");
39    let queue = device.new_command_queue().expect("command queue");
40
41    let command_buffer = queue.new_command_buffer().expect("command buffer");
42    let temporary_a =
43        State::temporary_with_buffer_size(&command_buffer, 32).expect("temporary state a");
44    let temporary_b =
45        State::temporary_with_buffer_size(&command_buffer, 64).expect("temporary state b");
46    let unique_count =
47        state_batch_increment_read_count(&[&temporary_a, &temporary_a, &temporary_b], 1);
48    assert_eq!(unique_count, 2);
49    assert_eq!(
50        temporary_a.resource_type_at_index(0),
51        state_resource_type::BUFFER
52    );
53    command_buffer.commit();
54    command_buffer.wait_until_completed();
55
56    let resource_list = StateResourceList::new().expect("resource list");
57    resource_list.append_buffer(16);
58    let persistent_state =
59        State::new_with_resource_list(&device, &resource_list).expect("persistent state");
60    assert_eq!(persistent_state.resource_count(), 1);
61    assert_eq!(persistent_state.buffer_size_at_index(0), 16);
62
63    let (gradient_buffer, gradient_vector) = vector_with_values(&device, &[0.1, -0.2]);
64    let (values_buffer, values_vector) = vector_with_values(&device, &[1.0, -1.0]);
65    let (result_buffer, result_vector) = vector_with_values(&device, &[0.0, 0.0]);
66    let optimizer = NNOptimizerStochasticGradientDescent::new(&device, 0.5).expect("sgd");
67    let base = optimizer.as_optimizer().expect("optimizer base");
68    assert_eq!(base.regularization_type(), nn_regularization_type::NONE);
69
70    let command_buffer = queue.new_command_buffer().expect("command buffer");
71    optimizer.encode_vector(
72        &command_buffer,
73        &gradient_vector,
74        &values_vector,
75        None,
76        &result_vector,
77    );
78    command_buffer.commit();
79    command_buffer.wait_until_completed();
80
81    let _ = gradient_buffer;
82    let _ = values_buffer;
83    let output = read_f32_values(&result_buffer, 2);
84    println!("{output:?}");
85}